Generating Rental Data for Car Sharing Relocation Simulations on the Example of Station-Based One-Way Car Sharing

Date
2017-01-04
Authors
Brendel, Alfred Benedikt
Rockenkamm, Christian
Kolbe, Lutz Maria
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
Ending Page
Alternative Title
Abstract
Developing sophisticated car sharing simulations is a major task to improve car sharing as a sustainable means of transportation, because new \ algorithms for enhancing car sharing efficiency are formulated using them. \ \ Simulations rely on input data, which is often gathered in car sharing systems or artificially generated. Real-world data is often incomplete and biased while artificial data is mostly generated based on initial assumptions. Therefore, developing new ways for generating testing data is an important task for future research. \ \ In this paper, we propose a new approach for generating car sharing data for relocation simulations by utilizing machine learning. Based on real-world data, we could show that a combined methods approach consisting of a Gaussian Mixture Model and two classification trees can generate appropriate artificial testing data.
Description
Keywords
car sharing, data generator, shared vehicle services, simulation, vehicle relocation
Citation
Extent
10 pages
Format
Geographic Location
Time Period
Related To
Proceedings of the 50th Hawaii International Conference on System Sciences
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.